Patterns of International Author Collaboration in Surge

Research Article

Austin J Surg. 2017; 4(5): 1114.

Patterns of International Author Collaboration in Surge

Chien TW¹, Chang Y², Chow JC³ and Chou W4,5*

¹Research Department, Chi-Mei Medical Center, Taiwan

²National Taiwan University School of Medicine, Taiwan

³Department of Pediatrics, Chi Mei Medical center, Taiwan

4Department of Physical Medicine and Rehabilitation, Chi Mei Medical Center, Tainan

5Department of Recreation and Health-Care Management & Institute of recreation, Industry Management, Chia Nan University of Pharmacy, Taiwan

*Corresponding author: Willy Chou, Department of Recreation and Health-Care Management & Institute of Recreation Industry Management, Chia Nan University of Pharmacy, Taiwan

Received: November 23, 2017; Accepted: December 15, 2017; Published: December 22, 2017


Objective: To investigate patterns of international author collaborations in surgery by collecting data from Medline and to visualize data using Google maps and Social Network Analysis (SNA).

Methods: Selecting 993 abstracts, author names, countries, and Medical Subject Headings (MESH) on December 2, 2017 from Medline based on journal of surgery in recent three years, we reported following features: (1) nation distribution for 1st author’s nationality; (2) prominent authors in the field of surgery, and (3) research features represented by paper’s MESH terms. We programmed Microsoft Excel VBA routines to extract data from Medline. Google Maps and SNAP ajek software were performed to display graphical representations with an easy-to-read feature for readers.

Results: We found that (1) the most number of papers in surgery are from nations of U.S. (413, 41.59%) and Japan (115, 11.58%); (2) the proactive authors in surgery are Hiroaki Nagano and Keith DLillemoe; (3) the most linked MESH terms are hepatectomy/adverse effects/methods and portal vein/anatomy & histology/diagnostic imaging/surgery.

Conclusion: Social network analysis provides wide and deep insight into the relationships among nations, coauthor collaborations, and MESH terms. The results can be provided to readers for future submission to journal in surgery.

Keywords: Abstract keywords; Authorship collaboration; Google Maps; Social network analysis; Medline


Surgery is a medical specialty that uses operative manual and instrumental techniques on a patient to investigate (or treat a pathological condition such as a disease or injury) to help improve bodily function or appearance or repair unwanted ruptured areas [1]. Many journals are included in surgery such as cardiac surgery, cardiothoracic surgery, colorectal surgery, endocrine surgery, general surgery, neurosurgery, obstetrics and gynecologic surgery, surgical oncology, ophthalmic surgery, oral and maxillofacial surgery, orthopedic surgery, head and neck surgery, pediatric surgery, plastic surgery, transplant surgery, thoracic surgery, vascular surgery, digestive surgery, trauma surgery, acute care surgery, laparoscopic surgery, bariatric and GI surgery, colorectal surgery, foregut surgery, colon and rectal Surgery, et al. Which nation plays the most important role in surgery is required to report. Meanwhile, which author published most papers in academics and which research domain is most prevalent in recent years are worthwhile to investigate.

In real world, any entity is rare independent in existence. Comorbid is defined in medicine as existing simultaneously with and usually being co-occurred with one another, such as screw sagittal angle related to stress on endplate of adjacent segments and lymph node metastasis associated with a gastric cancer patient [2,3]. In many situations, it is very hard to observe the association of two or more symptoms or entities existed in a system at a moment.

An apocryphal story often told to illustrate the concept of cooccurrence is about beer and diaper sales. It usually goes along with both beer and diaper sales which were strongly correlated [4-6] in a supermarket. All possible pairs of our observed objects can be combined to examine by using computer algorithms. However, we have not seen any demonstrate how to pick up the most possible pairs co-occurred in our datasets.

Social Network Analysis (SNA)

Social Network Analysis (SNA) [7-9] has been applied to authorship collaboration in recent years. Co-authorship among researchers can form a type of social network, called co-author network [7]. We are thus interested in using SNA to explore the closest relation in surgery from data we observed in Medline library.

Author collaborations and international relations

Many papers have been collected and saved in Medline library ( However, we have not seen any using Google maps to demonstrate their study results in literature even if computer scientists have put their hopes on those machine-learning algorithms, data mining or artificial intelligence to quantify research information [10,11]. Extracting papers from Medline is a way to release some important information in surgery using Google maps to increase the yield of knowledge from data generated in the course of inquiry [12- 14]. However, the messages on coauthor collaboration and the most productive author in surgery is still unclear.

Aims of the study

Our aims are to investigate patterns of international author collaborations in surgery by collecting data from Medline and to visualize results on following topics: (i) nation distribution in papers regarding surgery; (ii) the most prominent authors in surgery; (iii) the recent research domains defined by Medical Subject Headings (MESH) terms.


Data sources

We programmed Microsoft Excel VBA (Visual Basic for Applications) modules to extract abstracts and their corresponding coauthor names as well as MESH terms for each article on December 2, 2017 from Medicine National Institutes of Health (Medline) based on publications in recent three years. Only those abstracts published by the keyword surgery [journal] and labeled with Journal Article were included. Others like those labeled with Published Erratum, Editorial or without author nation name were excluded from this study. A total of 993 eligible abstracts were obtained from Medline since 2015.

Data arrangement to fit SNA requirement

Prior to visualize representations of interest in this study using SNA, we organized data in compliance with the SNA format and guidelines using Pajek software [15]. Microsoft Excel VBA was used to deal with data fitting to the SNA requirement.

Graphical representations to report

Author nations and their relations: A table (i.e. columns for publication years and rows for the 1st author nations) was made for presenting the distribution of nations regarding surgery. The bigger bubble means the more number of the nodes (i.e, nations, or MESH terms in this study). The wider line indicates the stronger relations between two nodes. Community clusters are filled with different colors in bubbles.

Keywords and MESH terms to present the research domain: If keywords represent the research domain, the stronger relations between two keywords can be highlighted by SNA, like the concept of co-occurrence about beer and diaper sales. The presentation for the bubble and line is interpreted similar to the previous section.

Statistical tools and data analyses

Google Maps [16] and SNAP ajek software [15] were used to display visualized representations for key authors and MESH terms in relation with surgery. Author-made Excel VBA modules were applied to organize data. Cluster coefficient represents the density of a network and is defined as CC= whereas n=the number of nodes in a network and m=the number of other connected nodes with a specific ego node. A significant lever (>1.96) is defined by t-value as the formula [=cc*v [(n-2)/(1-cc2)].


Author nations and their relations

A total of 993 eligible papers with complete author nations based on journal article since 2015 are shown in (Table 1). We can see that the most number of papers are from nations of U.S. (413, 41.59%) and Japan (115, 11.58%). The trend in the number of publications with authorship from countries is present in the column of growth in (Table 1). The diagram shown by SNA and Google Maps in (Figure 1) displays author collaboration among nations based on journal name involving surgery. The highest productive nations are from U.S. and Asia (Japan and China). Any nation collaborated with other nations are shown with a blue line. Interested authors are recommending clicking the bubble of interest to see details on a website at reference [17]. Several clusters are shown in (Figure 2), indicating that nations have a closer relation representing an identical color. The cluster represented by Sweden earns the highest density with a cc=0.84. In contrast, the lowest cc is shown in the network of US and Japan with a cc=0.0, respectively. We can see that any two nations have not connected with each other in the two clusters represented by US and Japan. The link on website was provided at reference [18].